Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles (2024.naacl-long)
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Kung-Hsiang Huang, Philippe Laban, Alexander Fabbri, Prafulla Kumar Choubey, Shafiq Joty, Caiming Xiong, Chien-Sheng Wu
| Challenge: | Existing studies on multi-document summarization focus on collating information that all sources agree upon, but the task of summarizing diverse information remains underexplored. |
| Approach: | They propose a task of summarizing diverse information encountered in multiple news articles encompassing the same event using a dataset curated by a large language model. |
| Outcome: | The proposed task aims to summarize diverse information in multiple news articles encompassing the same event . the proposed task is difficult due to its limited coverage and verbosity biases . |
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